Image processing method, image processing system, and non-transitory computer readable storage medium

ABSTRACT

An image processing method includes following operations: generating, by a processor, a sliding window for a target pixel in a plurality of pixels in image data; generating, by the processor, an original brightness histogram of the sliding window according to an original bit depth; generating, by the processor, a low-bit-depth brightness histogram of the sliding window according to a low bit depth; determining, by the processor, a target low-bit-depth range from the low-bit-depth brightness histogram according to the target pixel; extracting, by the processor, a partial original brightness histogram from the original brightness histogram according to the target low-bit-depth range; and performing, by the processor, a histogram equalization process on the partial original brightness histogram according to the original bit depth to generate a final brightness value of the target pixel.

RELATED APPLICATIONS

This application claims priority to Taiwanese Application Serial Number110146447, filed Dec. 10, 2021, which is herein incorporated byreference.

BACKGROUND Technical Field

The present disclosure relates to image processing technology. Moreparticularly, the present disclosure relates to an image processingmethod, an image processing system, and a non-transitory computerreadable storage medium.

Description of Related Art

With developments of technology, various image processing methods havebeen developed. In the various image processing methods, the histogramequalization process can be used to enhance the contrast of one image toimprove the visibility of the image. However, some current histogramequalization processes are unsuitable for the images with only onebrightness range or with more than two brightness ranges, or require alarge amount of calculation.

SUMMARY

Some aspects of the present disclosure are to provide an imageprocessing method. The image processing method includes followingoperations: generating, by a processor, a sliding window for a targetpixel in a plurality of pixels in image data; generating, by theprocessor, an original brightness histogram of the sliding windowaccording to an original bit depth; generating, by the processor, alow-bit-depth brightness histogram of the sliding window according to alow bit depth; determining, by the processor, a target low-bit-depthrange from the low-bit-depth brightness histogram according to thetarget pixel; extracting, by the processor, a partial originalbrightness histogram from the original brightness histogram according tothe target low-bit-depth range; and performing, by the processor, ahistogram equalization process on the partial original brightnesshistogram according to the original bit depth to generate a finalbrightness value of the target pixel.

Some aspects of the present disclosure are to provide an imageprocessing system. The image processing system includes a memory and aprocessor. The memory is configured to store image data. The processoris configured to perform following operations: generating a slidingwindow for a target pixel in a plurality of pixels in image data;generating an original brightness histogram of the sliding windowaccording to an original bit depth; generating a low-bit-depthbrightness histogram of the sliding window according to a low bit depth;determining a target low-bit-depth range from the low-bit-depthbrightness histogram according to the target pixel; extracting a partialoriginal brightness histogram from the original brightness histogramaccording to the target low-bit-depth range; and performing, a histogramequalization process on the partial original brightness histogramaccording to the original bit depth to generate a final brightness valueof the target pixel.

Some aspects of the present disclosure are to provide a non-transitorycomputer readable storage medium. The non-transitory computer readablestorage medium stores one or more computer programs. The one or morecomputer programs include instructions and a processor is configured toexecute the instructions. When the processor executes the instructions,the processor performs following operations: generating a sliding windowfor a target pixel in a plurality of pixels in image data; generating anoriginal brightness histogram of the sliding window according to anoriginal bit depth; generating a low-bit-depth brightness histogram ofthe sliding window according to a low bit depth; determining a targetlow-bit-depth range from the low-bit-depth brightness histogramaccording to the target pixel; extracting a partial original brightnesshistogram from the original brightness histogram according to the targetlow-bit-depth range; and performing, a histogram equalization process onthe partial original brightness histogram according to the original bitdepth to generate a final brightness value of the target pixel.

As described above, in the present disclosure, the low-bit-depthbrightness histogram is generated first, the partial original brightnesshistogram is extracted from the original brightness histogram accordingto the target low-bit-depth range including the target pixel, and thehistogram equalization process is performed on the extracted partialoriginal brightness histogram according to the original bit depth.Accordingly, the present disclosure can be applied to the image withonly one brightness range or with more than two brightness ranges, andcan achieve the effect of reducing hardware area, reducing powerconsumption, or reducing the amount of calculation. In addition, sincethe process of generating the low-bit-depth brightness histogram alsohas the effect of low-pass filtering, there is no need to designadditional low-pass filter circuit or to perform additional low-passfiltering calculation in the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure can be more fully understood by reading the followingdetailed description of the embodiment, with reference made to theaccompanying drawings as follows:

FIG. 1 is a schematic diagram of an image processing system according tosome embodiments of the present disclosure.

FIG. 2 is a flow diagram of an image processing method according to someembodiments of the present disclosure.

FIG. 3 is a schematic diagram of one operation in FIG. 2 according tosome embodiments of the present disclosure.

FIG. 4 is a schematic diagram of an original brightness histogram and alow-bit-depth brightness histogram according to some embodiments of thepresent disclosure.

FIG. 5 is a schematic diagram of one operation in FIG. 2 according tosome embodiments of the present disclosure.

FIG. 6 is a schematic diagram of one operation in FIG. 2 according tosome embodiments of the present disclosure.

FIG. 7 is a schematic diagram of one operation in FIG. 2 according tosome embodiments of the present disclosure.

FIG. 8 is a schematic diagram of an image processing system according tosome embodiments of the present disclosure.

DETAILED DESCRIPTION

In the present disclosure, “connected” or “coupled” may refer to“electrically connected” or “electrically coupled.” “Connected” or“coupled” may also refer to operations or actions between two or moreelements.

Reference is made to FIG. 1 . FIG. 1 is a schematic diagram of an imageprocessing system 100 according to some embodiments of the presentdisclosure. As illustrated in FIG. 1 , the image processing system 100includes a memory 110, a memory 120, a processor 140, and a displaydevice 160. The memory 110 is coupled to the memory 120. The processor140 is coupled to the memory 120 and the display device 160.

In some embodiments, the memory 110 can be implemented by a DynamicRandom Access Memory (DRAM). The memory 120 can be implemented by aStatic Random Access Memory (SRAM). The processor 140 can be implementedby a digital logic circuit. For example, the processor 140 can be adigital logic circuit which is designed by a register-transfer level(RTL) method. In other words, these embodiments are implemented by adigital hardware manner. The display device 160 can be implemented by adisplay panel or a touch display panel.

References are made to FIG. 1 and FIG. 2 . FIG. 2 is a flow diagram ofan image processing method 200 according to some embodiments of thepresent disclosure.

As illustrated in FIG. 2 , the image processing method 200 includesoperation S210, operation S220, operation S230, operation S240,operation S250, operation S260, and operation S270.

In some embodiments, the image processing method 200 can be implementedto the image processing system 100 in FIG. 1 , but the presentdisclosure is not limited thereto. For better understanding, followingparagraphs are described with reference with FIG. 1 .

Reference is also made to FIG. 3 . FIG. 3 is a schematic diagram ofoperation S210 in FIG. 2 according to some embodiments of the presentdisclosure. In operation S210, the processor 140 generates slidingwindows W1-W4 for target pixels P1-P4 in pixels in image data IMGrespectively, in which the pixel P1 is disposed at a first row and afirst column, the pixel P2 is disposed at the first row and a secondcolumn, the pixel P3 is disposed at the first row and a third column,and the pixel P4 is disposed at a second row and the first column. Insome embodiments, the memory 110 is configured to store the entire imagedata IMG, and the memory 120 is configured to temporarily store localimage data. For example, when it intends to generate the sliding windowW1, the image data in the range of the sliding window W1 is transmitfrom the memory 110 to the memory 120 and is temporarily stored in thememory 120 for the processor 140 to process. Since the image data in therange of the sliding window W1 is stored in the memory 120 in row by row(line by line) manner, the memory 120 works as a line buffer.

As illustrated in FIG. 3 , at first, the processor 140 determines thesliding window W1 according to the target pixel P1, in which the targetpixel P1 is disposed at the center of the sliding window W1. The slidingwindow W1 can be in a shape of a rectangle. The length or the width ofthe sliding window W1 can be designed according to actual requirements.The brightness values in the sliding window W1 but outside the imagedata IMG can be compensated by a repeating method, a zero paddingmethod, or a mapping method.

Then, the processor 140 can determine the sliding windows W2-W4according to the target pixels P2-P4 respectively, in which the targetpixels P2-P4 are disposed at the centers of the sliding windows W2-W4respectively. Similarly, the brightness values in the sliding windowsW2-W4 but outside the image data IMG can be compensated by the repeatingmethod, the zero padding method, or the mapping method.

For ease and better understanding, FIG. 3 merely takes four targetpixels P1-P4 of the image data ING as an example, and other pixels havesimilar operations. By applying the operations above to all pixels inthe image data IMG, it can acquire the sliding windows of the all pixelsin the image data IMG.

The following paragraphs take the target pixel P1 and the correspondingsliding window W1 as an example, and other pixels have similaroperations.

Reference is made to FIG. 4 . FIG. 4 is a schematic diagram of anoriginal brightness histogram 400A and a low-bit-depth brightnesshistogram 400B according to some embodiments of the present disclosure.

In operation S220, the processor 140 generates the original brightnesshistogram 400A of the sliding window W1 according to an original bitdepth. In some embodiments, the original bit depth corresponds, forexample, 8 bits, but the present disclosure is not limited thereto. Inother words, when the original bit depth corresponds 8 bits, an originalbrightness value of each of the pixels corresponds 256 (i.e., 2⁸) levels(e.g., 0-255 levels). The processor 140 can generate the originalbrightness histogram 400A according to the original brightness values(original bit depth) of the all pixels in the sliding window W1.

In operation S230, the processor 140 generates the low-bit-depthbrightness histogram 400B of the sliding window W1 according to the lowbit depth. In some embodiments, the low bit depth is smaller than theoriginal bit depth. For example, the low bit depth corresponds, forexample, 4 bits, but the present disclosure is not limited thereto. Inother words, when the low bit depth corresponds 4 bits, a low-bit-depthbrightness value of each of the pixels corresponds 16 (i.e., 2⁴) levels(e.g., 0-15 levels). In some embodiments, the processor 140 can dividethe original brightness value of each pixel by 16 and perform a rounddown process to acquire the low-bit-depth brightness value of the eachpixel. However, based on the round down process above, when an originalbrightness value is an integer in a range from 48 to 63, thecorresponding low-bit-depth brightness value is 4. Then, the processor140 can generate the low-bit-depth brightness histogram 400B accordingto the low-bit-depth brightness values (low-bit-depth) of all pixels inthe sliding window W1. Operation S230 is a “down sampling” process. Inother words, compared to the original brightness histogram 400A, linesin the low-bit-depth brightness histogram 400B change smoothly.

Reference is made to FIG. 5 . FIG. 5 is a schematic diagram of operationS240 in FIG. 2 according to some embodiments of the present disclosure.In operation S240, the processor 140 divides the low-bit-depthbrightness histogram 400B.

In some embodiments, the processor 140 can determine two boundary pointsA-B and a local boundary point C corresponding to at least one localminimum value in the low-bit-depth brightness histogram 400B. Then, theprocessor 140 can divide the low-bit-depth brightness histogram 400Binto a low-bit-depth range DV1 and a low-bit-depth range DV2 accordingto the brightness values (e.g., a gray-scale value 0 and a gray-scalevalue 15) corresponding to the two boundary points A-B and a brightnessvalue (e.g., a gray-scale value 6) corresponding to the local boundarypoint C. The low-bit-depth range DV1 covers a range from the boundarypoint A to the local boundary point C. The low-bit-depth range DV2covers a range from the local boundary point C to the boundary point B.

In some embodiments, the vertical axis value N of the local boundarypoint C meets the following two conditions

N≤(N−1) and N≤(N+1)   condition 1

N(≠N=1)and N≠(N+1)   condition 2

in which N is the vertical axis value (number of occurrence) of thelocal boundary point C (i.e., there are N pixels having the brightnessvalue corresponding to the local boundary point C), (N+1) is thevertical axis value (number of occurrence) of a right-hand side pointadjacent to the local boundary point C, and (N−1) is the vertical axisvalue (number of occurrence) of a left-hand side point adjacent to thelocal boundary point C.

Reference is made to FIG. 6 . FIG. 6 is a schematic diagram of operationS250 in FIG. 2 according to some embodiments of the present disclosure.

In operation S250, the processor 140 determines the low-bit-depth rangeDV1 from the low-bit-depth brightness histogram 400B according to thetarget pixel P1. As illustrated in FIG. 6 , since the low-bit-depthbrightness value of the target pixel P1 is in the low-bit-depth rangeDV1, the processor 140 determines that the low-bit-depth range DV1 isthe target low-bit-depth range.

Reference is made to FIG. 7 . FIG. 7 is a schematic diagram of operationS260 in FIG. 2 according to some embodiments of the present disclosure.

In operation S260, the processor 140 can extract the partial originalbrightness histogram 400A′ from the original brightness histogram 400Aaccording to the target low-bit-depth range DV1. In some embodiments,the processor 140 can align (map) the low-bit-depth brightness histogram400B with the original brightness histogram 400A. As illustrated in FIG.7 , according to the low-bit-depth range DV1 and the low-bit-depth rangeDV2, the original brightness histogram 400A can be divided into anoriginal-bit-depth range DV1′ and an original-bit-depth range DV2′, inwhich the original-bit-depth range DV1′ corresponds to the low-bit-depthrange DV1, and the original-bit-depth range DV2′ corresponds to thelow-bit-depth range DV2. Then, the processor 140 can extract theoriginal-bit-depth range DV1′ from the original brightness histogram400A according to the determined target low-bit-depth range DV1 inoperation S250 to be the partial original brightness histogram 400A′. Inother words, the original-bit-depth range DV1′ is remained in thepartial original brightness histogram 400A′, and the original-bit-depthrange DV2′ is removed. For example, the vertical axis values (number ofoccurrence) in the original-bit-depth range DV2′ can be set to be 0.

In operation S270, the processor 140 performs the histogram equalizationprocess on the partial original brightness histogram 400A′ according tothe original bit depth to generate a final brightness value of thetarget pixel P1. Since the partial original brightness histogram 400A′corresponds to the original bit depth (e.g., 8-bit depth/256 levels),the processor 140 performs the histogram equalization process on thepartial original brightness histogram 400A′ according to the originalbit depth to generate the final brightness value of the target pixel P1.Then, the processor 140 generates a final image according to the finalbrightness values of the pixels for the display device 160 to display.The detailed operations of the histogram equalization process aredescribed in following paragraphs.

First, the processor 140 performs a cumulative distribution function(CDF) process on the partial original brightness histogram 400A′ tocalculate cumulative distribution function values of all gray-scalevalues in the partial original brightness histogram 400A′.

Then, the processor 140 acquires the equalized gray-scale valuesaccording to formula (1):

$\begin{matrix}{{{newHist}(n)} = {{round}\left( {\frac{{{cdf}(n)} - {cdf}_{\min}}{{cdf}_{\max} - {cdf}_{\min}} \times \left( {L - 1} \right)} \right)}} & (1)\end{matrix}$

in which L is a level number corresponding to the original bit depth (Lis 256 when the original bit depth corresponds to 8 bits), cdf_(min) isa minimum value among all non-zero values in the cumulative distributionfunction values, cdf_(max) is a maximum value among all non-zero valuesin the cumulative distribution function values, cdf(n) is a targetgray-scale value (before equalization) in the partial originalbrightness histogram 400A′ and n is an index value, newHist(n) is a newequalized gray-scale value of the target gray-scale value, the roundfunction performs a round off process on the values such that the finalvalues are integer values.

In the present disclosure, the histogram equalization process isperformed on the partial original brightness histogram 400A′ whichcorresponds to the original bit depth. Accordingly, the presentdisclosure can still obtain a higher resolution range.

Some related approaches (e.g., Otsu binarization approach) need a largeamount of recursion calculation and the brightness histogram is merelydivided into two ranges. These approaches are unsuitable for the imageswith only one brightness range or with more than two brightness ranges.

Some other approaches directly scan all local minimum values in theoriginal brightness histogram which corresponds to the original bitdepth. However, as the original bit depth becomes deeper and deeper, theamount of scanning or calculation for the original brightness histogrambecomes larger and larger. These are not conducive for the imageprocessing process.

Compared to the aforementioned approaches, in the present disclosure,the processor 140 generates the low-bit-depth histogram first, extractsthe partial original brightness histogram 400A′ from the originalbrightness histogram 400A according to the target low-bit-depth rangeDV1 including the target pixel P1, performs the histogram equalizationprocess on the partial original brightness histogram 400A′ according tothe original bit depth. Since the low-bit-depth ranges in the presentdisclosure are not limited to only two (although FIG. 5 takes twolow-bit-depth ranges DV1-DV2 as an example), the present disclosure canbe applied to the image with more than two brightness ranges.

In addition, as described above, the process of changing from theoriginal bit depth to the low bit depth in operation S230 can beregarded as “down-sampling.” Compared to the original brightnesshistogram 400A, it takes less calculation to find the local boundarypoint C corresponding to the local minimum values on the low-bit-depthbrightness histogram 400B. Accordingly, the processor 140 in the presentdisclosure occupies a smaller hardware area (e.g., the numbers ofcomparators, multiplexers, adders, and multipliers used to find thelocal minimum values and perform the low-pass filtering process can bereduced) and has low power consumption. In addition, since thelow-bit-depth brightness histogram 400B is relatively smooth, it canavoid irrelevant noise.

In addition, since “down-sampling” has the effect of low-pass filtering,the processor 140 can be designed without additional low-pass filtercircuit or without additional low-pass filtering calculation.

Reference is made to FIG. 7 again. In some embodiments, the process ofaligning (mapping) the low-bit-depth brightness histogram 400B with theoriginal brightness histogram 400A by the processor 140 inaforementioned operation S260 further includes performing a boundaryadjustment process according to the original bit depth.

As illustrated in FIG. 7 , since the low-bit-depth range DV1 in thelow-bit-depth brightness histogram 400B is used to extract the partialoriginal brightness histogram 400A′, the processor 140 can perform theboundary adjustment process on the local boundary point C (thelow-bit-depth brightness is 6) which is at the right-hand side of thelow-bit-depth range DV1.

As described above, the low-bit-depth brightness value is acquired bydividing the original brightness value by 16 and performing the rounddown process. Effectively, one low-bit-depth brightness value (e.g., 6)corresponds to multiple original brightness values (e.g., integers from96 to 111). In this situation, when the low-bit-depth brightness value(e.g., 6) of the local boundary point C is multiplied by 16 to acquirethe corresponding gray-scale value in the original brightness histogram400A, only one integer (e.g., 96) is acquired and other integers (e.g.,97-111) are not covered.

Based on problems above, the processor 140 performs the boundaryadjustment process according to formula (2) below:

S2=S1×2^((N2−N1))+(2^((N2−N1)9)−1)   (2)

in which S1 is the gray-scale value of one boundary point in thelow-bit-depth brightness histogram 400B, N2 is the original bit depth,N1 is the low bit depth, and S2 is the corresponding gray-scale value inthe original brightness histogram 400A.

As illustrated in FIG. 7 , the local boundary point C has the gray-scalevalue 6 (i.e., S1), the original bit depth corresponds, for example, 8(i.e., S2), and the low bit depth corresponds, for example, 4 (i.e.,N1). Based on formula (2) above, P2 is 111. In other words, the localboundary point C in the low-bit-depth brightness histogram 400B isaligned to the gray-scale value 111 in the original brightness histogram400A. Accordingly, 97-111 can be covered to extract appropriate theoriginal-bit-depth range DV1′ from the original brightness histogram400A.

The above description of the image processing method 200 includesexemplary operations, but the operations of the image processing method200 are not necessarily performed in the order described. The order ofthe operations of the image processing method 200 disclosed in thepresent disclosure are able to be changed, or the operations are able tobe executed simultaneously or partially simultaneously as appropriate,in accordance with the spirit and scope of various embodiments of thepresent disclosure.

Reference is made to FIG. 8 . FIG. 8 is a schematic diagram of an imageprocessing system 800 according to some embodiments of the presentdisclosure. In some embodiments, the image processing method 200 can beimplemented to the image processing system 800 in FIG. 8 .

As illustrated in FIG. 8 , the image processing system 800 includes amemory 810, a memory 820, a processor 840, and a display device 860. Theprocessor 840 is coupled to the memory 810, the memory 820, and thedisplay device 860.

In some embodiments, the memory 810 can be implemented by a dynamicrandom access memory to store the aforementioned image data IMG. Thememory 820 can be implemented by a non-transitory computer readablestorage medium and configured to store one or more computer programs CPincluding a plurality of instructions. The processor 840 can beimplemented by a central processor or a microprocessor. When thecomputer programs CP is executed by the processor 840, theaforementioned image processing method 200 is performed. In other words,these embodiments utilize a software manner to implement the imageprocessing method 200. The display device 860 can be implemented by adisplay panel or a touch display panel.

In the embodiments which are mainly implemented by software, it can beapplied to the image with more than two brightness ranges, can reducethe amount of calculation, and can improve the calculation speed. Inaddition, there is no need to perform additional low-pass filteringcalculation.

As described above, in the present disclosure, the low-bit-depthbrightness histogram is generated first, the partial original brightnesshistogram is extracted from the original brightness histogram accordingto the target low-bit-depth range including the target pixel, and thehistogram equalization process is performed on the extracted partialoriginal brightness histogram according to the original bit depth.Accordingly, the present disclosure can be applied to the image withonly one brightness range or with more than two brightness ranges, andcan achieve the effect of reducing hardware area, reducing powerconsumption, or reducing the amount of calculation. In addition, sincethe process of generating the low-bit-depth brightness histogram alsohas the effect of low-pass filtering, there is no need to designadditional low-pass filter circuit or to perform additional low-passfiltering calculation in the present disclosure.

Although the present disclosure has been described in considerabledetail with reference to certain embodiments thereof, other embodimentsare possible. Therefore, the spirit and scope of the appended claimsshould not be limited to the description of the embodiments containedherein. It will be apparent to those skilled in the art that variousmodifications and variations can be made to the structure of the presentdisclosure without departing from the scope or spirit of the disclosure.In view of the foregoing, it is intended that the present disclosurecover modifications and variations of this disclosure provided they fallwithin the scope of the following claims.

What is claimed is:
 1. An image processing method, comprising:generating, by a processor, a sliding window for a target pixel in aplurality of pixels in image data; generating, by the processor, anoriginal brightness histogram of the sliding window according to anoriginal bit depth; generating, by the processor, a low-bit-depthbrightness histogram of the sliding window according to a low bit depth;determining, by the processor, a target low-bit-depth range from thelow-bit-depth brightness histogram according to the target pixel;extracting, by the processor, a partial original brightness histogramfrom the original brightness histogram according to the targetlow-bit-depth range; and performing, by the processor, a histogramequalization process on the partial original brightness histogramaccording to the original bit depth to generate a final brightness valueof the target pixel.
 2. The image processing method of claim 1, whereinthe low bit depth is smaller than the original bit depth.
 3. The imageprocessing method of claim 1, wherein determining, by the processor, thetarget low-bit-depth range from the low-bit-depth brightness histogramaccording to the target pixel comprises: determining, by the processor,a plurality of boundary points and a local boundary point correspondingto at least one local minimum value according to the low-bit-depthbrightness histogram; determining, by the processor, a plurality oflow-bit-depth ranges according to the boundary points and the localboundary point; and determining, by the processor, the targetlow-bit-depth range from the low-bit-depth ranges according to alow-bit-depth brightness value of the target pixel.
 4. The imageprocessing method of claim 1, further comprising: performing, by theprocessor, a boundary adjustment process according to the original bitdepth.
 5. The image processing method of claim 4, wherein the processorperforms the boundary adjustment process according to:S2=S1×2^((N2−N1))+(2^((N2−N1))−1) wherein S1 is a gray-scale value of aboundary point in the low-bit-depth brightness histogram, N2 is theoriginal bit depth, N1 is the low bit depth, and S2 is a correspondinggray-scale value in the original brightness histogram.
 6. The imageprocessing method of claim 1, further comprising: generating, by theprocessor, a final image according to the final brightness value of eachof the pixels for a display device to display.
 7. An image processingsystem, comprising: a memory configured to store image data; and aprocessor configured to perform following operations: generating asliding window for a target pixel in a plurality of pixels in imagedata; generating an original brightness histogram of the sliding windowaccording to an original bit depth; generating a low-bit-depthbrightness histogram of the sliding window according to a low bit depth;determining a target low-bit-depth range from the low-bit-depthbrightness histogram according to the target pixel; extracting a partialoriginal brightness histogram from the original brightness histogramaccording to the target low-bit-depth range; and performing a histogramequalization process on the partial original brightness histogramaccording to the original bit depth to generate a final brightness valueof the target pixel.
 8. The image processing system of claim 7, whereinthe processor is a digital logic circuit designed by a register-transferlevel method, and the memory is a line buffer.
 9. The image processingsystem of claim 7, wherein the low bit depth is smaller than theoriginal bit depth.
 10. The image processing system of claim 7, whereinthe processor is further configured to perform following operations:determining a plurality of boundary points and a local boundary pointcorresponding to at least one local minimum value according to thelow-bit-depth brightness histogram; determining a plurality oflow-bit-depth ranges according to the boundary points and the localboundary point; and determining the target low-bit-depth range from thelow-bit-depth ranges according to a low-bit-depth brightness value ofthe target pixel.
 11. The image processing system of claim 7, whereinthe processor is further configured to perform following operation:performing a boundary adjustment process according to the original bitdepth.
 12. The image processing system of claim 11, wherein theprocessor performs the boundary adjustment process according to:S2=S1×2^((N2−N1))+(2^((N2−N1))−1) wherein S1 is a gray-scale value of aboundary point in the low-bit-depth brightness histogram, N2 is theoriginal bit depth, N1 is the low bit depth, and S2 is a correspondinggray-scale value in the original brightness histogram.
 13. The imageprocessing system of claim 7, wherein the processor is configured togenerate a final image according to the final brightness value of eachof the pixels for a display device to display.
 14. A non-transitorycomputer readable storage medium storing one or more programs, whereinthe one or more programs comprise instructions and a processor isconfigured to execute the instructions, wherein when the processorexecutes the instructions, the processor performs following operations:generating a sliding window for a target pixel in a plurality of pixelsin image data; generating an original brightness histogram of thesliding window according to an original bit depth; generating alow-bit-depth brightness histogram of the sliding window according to alow bit depth; determining a target low-bit-depth range from thelow-bit-depth brightness histogram according to the target pixel;extracting a partial original brightness histogram from the originalbrightness histogram according to the target low-bit-depth range; andperforming a histogram equalization process on the partial originalbrightness histogram according to the original bit depth to generate afinal brightness value of the target pixel.
 15. The non-transitorycomputer readable storage medium of claim 14, wherein the low bit depthis smaller than the original bit depth.
 16. The non-transitory computerreadable storage medium of claim 14, wherein the processor is furtherconfigured to perform following operations: determining a plurality ofboundary points and a local boundary point corresponding to at least onelocal minimum value according to the low-bit-depth brightness histogram;determining a plurality of low-bit-depth ranges according to theboundary points and the local boundary point; and determining the targetlow-bit-depth range from the low-bit-depth ranges according to alow-bit-depth brightness value of the target pixel.
 17. Thenon-transitory computer readable storage medium of claim 14, wherein theprocessor is further configured to perform following operation:performing a boundary adjustment process according to the original bitdepth.
 18. The non-transitory computer readable storage medium of claim17, wherein the processor performs the boundary adjustment processaccording to:S2=S1×2^((N2−N1))+(2^((N2−N1))−1) wherein S1 is a gray-scale value of aboundary point in the low-bit-depth brightness histogram, N2 is theoriginal bit depth, N1 is the low bit depth, and S2 is a correspondinggray-scale value in the original brightness histogram.